Moments that matter

Learning proactively: WHO, IHI and cross‑sector principles

WHO’s patient safety frameworks emphasise a systems approach, just culture, and learning from “unsafe conditions, hazards and near misses” as part of an integrated safety management system. IHI’s work on adverse event detection and trigger tools reinforces the need to move from reactive investigation of harm towards proactive surveillance for risk signals across the care pathway.

Cross‑sector reflections on NM, including Woodier’s work, highlight several recurring principles: NM often share the same underlying causes as serious incidents, they frequently precede them in time, and they reveal “latent conditions” in design, resourcing, and culture that are not visible from rare catastrophic events alone. Learning from NM therefore requires more than counting; it demands structured analysis, involvement of those closest to the work, and system‑level responses across people, processes, and technology.

These principles align closely with SHOT’s approach, which couples descriptive analysis of NM patterns (such as the predominance of WBIT) with practical recommendations on identification processes, training, and the use of technologies such as barcode scanning. When applied consistently, this turns NM into a continuous feedback loop for system improvement rather than isolated “lucky escapes”.

Evidence from studies on NM reporting reducing transfusion errors

Studies consistently show that structured NM reporting reduces transfusion risk by exposing systemic gaps early and guiding targeted interventions. Dedicated systems such as MERS TM, which captured 819 events in 19 months, demonstrated that NM occur five times more often than actual errors and that 68% of errors were intercepted before blood was issued, enabling teams to identify patterns such as wrong-patient samples and mislabelling and to track whether corrective actions reduce recurrence.

Sixteen years of SHOT data show that analysing NM patterns has directly shaped national practice, strengthening patient identification standards, sampling policies, training, and supporting the adoption of electronic positive patient identification.

Crucially, learning from NM is as valuable as learning from actual incidents but without the psychological and physical harm associated with them. Lessons from NM drive improvements across healthcare organisations by enabling shared learning and supporting risk-mitigating actions. To achieve this, organisations must foster a culture where staff feel psychologically safe to report without fear of blame or negative consequences, supported by system-focused rather than person-focused investigations. However, the 2023 SHOT and UKTLC transfusion laboratory culture survey highlighted persistent concerns, including laboratory staff experiencing incivility or disciplinary action after raising safety issues or submitting incident reports. The report includes recommendations to help organisations build psychological safety, and it emphasises that NM investigation must be fully embedded in policy and resourced appropriately so staff can understand—and act on—their critical role in improving patient safety.

Mechanisms by which NM reporting reduces risk Across these sources, several mechanisms link NM reporting to reductions in transfusion errors:

• Identification of high‑risk steps: NM data reveal exactly where pre‑transfusion processes fail most often, allowing targeted redesign of sampling, labelling and checking procedures.
• Detection of latent conditions: Aggregated NM expose system issues such as staffing gaps, workload pressures, poor layout, or confusing forms before they cause harm – this is evident from the human factors principles-based analysis of NM reported to SHOT.
• Monitoring impact of interventions: Systems such as MERS‑TM were explicitly used to “monitor changes in frequency after corrective action”, enabling teams to see whether specific interventions reduced particular error types
• Culture and vigilance: No‑fault reporting and visible learning from NM support a stronger safety culture, which is associated in broader patient‑safety literature with lower serious error rates

Strategies to boost NM reporting rates in hospitals

To boost NM reporting, organisations must tackle the main barriers—fear of blame, lack of clarity, weak leadership support, and clunky systems—by creating a just, learning culture where staff feel safe and valued for speaking up. Clear no-blame messages, visible appreciation for “good catches,” and simplified, integrated reporting systems make reporting easier and less intimidating, while options for anonymous submissions further reduce fear. Staff need regular, practical education on what constitutes a NM and why it matters, reinforced through huddles, induction, and real examples such as WBIT. Crucially, timely feedback, simple dashboards, and recognition of individuals and teams show that reporting leads to action, strengthening trust and closing the learning loop. Together, these strategies make NM reporting quicker, safer, and genuinely meaningful.

NM are among the most valuable but most likely underused sources of safety intelligence in healthcare. SHOT data clearly show that NM, particularly WBIT, provide early warnings of the very failures that cause serious transfusion incidents. Evidence from haemovigilance systems, structured reporting tools, and hospital-level studies demonstrates that learning from NM reduces risk, strengthens safety culture, and improves resource use. By embedding NM into everyday clinical and laboratory improvement—making reporting simple, analysis routine, actions visible, and feedback timely—healthcare organisations can move upstream of harm and deliver safer transfusion practice and safer care overall.